Chinese contentScientist World:把 1000 篇论文变成 AI 科研可执行环境
把 1000 篇论文做成 AI 科学家能跑的实验环境,还测出它在 74% 场景下跑赢人类作者,训练数据也开源了,做科研智能体的别错过。
把 1000 篇论文做成 AI 科学家能跑的实验环境,还测出它在 74% 场景下跑赢人类作者,训练数据也开源了,做科研智能体的别错过。
这篇论文给现有的 AI 科研创意系统加了个“改哪、怎么改”的决策层,靠反事实推演选修改方案,消融数据挺扎实,做科研智能体的可以看看。
训练科研智能体最缺的就是能跑、能验证的环境,这套流水线从代码仓库自动造出近 10 万个,还把 Qwen3.5 训出了跨基准提升。
The key insight is that budget allocation strategy, not raw model capability, drives research-agent performance — treating experiments as a resource-allocation problem rather than a fixed pipeline. Teams building autonomous research or discovery agents can apply this explore-then-concentrate policy to cut token costs while improving output quality. It compares directly against AutoResearch on FIRE-Bench, giving a concrete benchmark baseline for evaluating competing agentic research frameworks.